Garrett M. Steede (author), Courtney Meyers (author), Nan Li (author), Erica Irlbeck (author), Sherice Gearhart (author), and Texas Tech University; University of Minnesota - Twin Cities
Format:
Journal article
Publication Date:
2018
Published:
USA
Location:
Agricultural Communications Documentation Center, Funk Library, University of Illinois Box: 149 Document Number: D10103
Article 4; pgs. 1-16, On January 1, 2017, the final rule of the Veterinary Feed Directive (VFD) was put into place requiring
antibiotics approved for both humans and animals to be discontinued for growth promotion. This change was
brought on by the role growth promoters in livestock production play in the development of antibiotic
resistance. Antibiotic resistance increases the costs associated with human health care by increasing the length
of stays in the hospital and requiring more intensive medical care for patients. The purpose of this study was to
explore sentiment and characteristics of social media content and the characteristics of the key influencers
whose opinions had the greatest amount of reach on social media in regard to antibiotic use in livestock and
antibiotic resistance. Nuvi, a social media monitoring program, provided sentiment for each tweet and coded
64.8% of the content (n = 129) as negative compared to 38.2% (n = 76) humans coded as negative. The
contrast between human coders and Nuvi indicates there could be discrepancies between how Nuvi codes
content and the way a human might interpret the content. No key influencer discussed antibiotic use in
livestock positively. Findings suggest agricultural communicators should not rely completely on the output
from sentiment analysis programs to evaluate how the public discusses issues related to agriculture,
particularly controversial issues. Further, agricultural communications practitioners should prioritize
monitoring the content shared by key influencers in an effort to better understand the content being shared by
the most influential users. Recommendations for future research are provided.
4 pages., Online via AgEconSearch, Authors explain the basic concepts of Internet+ and big data, analyze the main problems in the application of big data technology in agricultural informationization, summarize corresponding solutions from the aspects of government guidance, financial input, open sharing of agricultural big data, big data storage and processing, data mining, etc., and describe prospects ahead in the province.
Summarizes results of a non-farmer survey documenting how each of five stages of the agricultural and food business value chain is evolving in terms of data collection and use.
